Comparing Neural Networks and ARMA Models in Artificial Stock Market

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F11%3A10102906" target="_blank" >RIV/00216208:11320/11:10102906 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985556:_____/11:00361537

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Comparing Neural Networks and ARMA Models in Artificial Stock Market

Popis výsledku v původním jazyce

We create a new way of comparing models for forecasting stock prices. Our idea was to create a simple game in which the individual models would compete against each other. We were inspired by the heterogeneous agent models and we created an artificial market. Models act in our artificial market as a forecasting strategies of each agent who trades on the market. Each agent uses his own model for predicting future prices of risky asset and its dividends. Delayed prices of risky asset and dividends provided the basis for predictions. The way how agents trade affects the price of risky asset, which in turn influences their expectations and therefore their decisions whether to buy or sell. Moreover, each agent can recalculate his strategy, if he is not satisfied with its performance. So the forecasting strategies and the artificial market evolve side by side. The models we confront are neural networks VARMA models. The winning model is the one which earns the most money.

Název v anglickém jazyce

Comparing Neural Networks and ARMA Models in Artificial Stock Market

Popis výsledku anglicky

We create a new way of comparing models for forecasting stock prices. Our idea was to create a simple game in which the individual models would compete against each other. We were inspired by the heterogeneous agent models and we created an artificial market. Models act in our artificial market as a forecasting strategies of each agent who trades on the market. Each agent uses his own model for predicting future prices of risky asset and its dividends. Delayed prices of risky asset and dividends provided the basis for predictions. The way how agents trade affects the price of risky asset, which in turn influences their expectations and therefore their decisions whether to buy or sell. Moreover, each agent can recalculate his strategy, if he is not satisfied with its performance. So the forecasting strategies and the artificial market evolve side by side. The models we confront are neural networks VARMA models. The winning model is the one which earns the most money.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

<a href="/cs/project/GD402%2F09%2FH045" target="_blank" >GD402/09/H045: Nelineární dynamika v peněžní ekonomii a financích. Teorie a empirické modely.</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Bulletin of the Czech Econometric Society

ISSN

1212-074X

e-ISSN

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Svazek periodika

18

Číslo periodika v rámci svazku

28

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

13

Strana od-do

53-65

Kód UT WoS článku

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EID výsledku v databázi Scopus

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